Description
Course info
Level
Beginner
Updated
Mar 4, 2021
Duration
1h 7m
Description

There are many deep learning frameworks to choose from. Caffe, which is written with speed, expression, and modularity in mind, is a great contender to be your framework of choice. In this course, Deep Learning with Caffe, you’ll learn to use Caffe to build a convolutional neural network that will help you classify a given set of images.

First, you’ll explore what deep learning is, how it differs from traditional machine learning, and how a neural network functions. Next, while building your very own convolutional neural network, you’ll learn how to prepare data for deep learning, define the model and solver, and train the model. Finally, you’ll discover how to improve the performance of your model using transfer learning.

When you’re finished with this course, you’ll have the skills and knowledge necessary to build your very own CNN using Caffe that’ll help solve custom image classification problems.

About the author
About the author

Pratheerth is a freelance Data Scientist who has entered the field after an eclectic mix of educational and work experiences.

More from the author
Building Visualizations with MATLAB
Intermediate
41m
Sep 25, 2020
Perform Predictive Modeling with MATLAB
Advanced
1h 11m
Jun 29, 2020
More courses by Pratheerth Padman
Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hey, everyone, my name is Pratheerth Padman, and welcome to my course, Deep Learning with Caffe. Currently, I'm a freelance data scientist. I used to work in manufacturing, but because of my love for all things data, I completely pivoted to data science. If you've ever dabbled with artificial intelligence of any sort, you would have definitely heard about deep learning. It is pretty much state of the art and has applications in so many fields in so many different ways that it is quite difficult to wrap your head around. In this course, we'll be focusing on the image classification aspect of deep learning. There are many deep learning frameworks to choose from, and Caffe, which is written with speed, expression, and modularity in mind, is a great contender to be offering work of choice. Some of the major topics that we'll cover include demystifying deep learning and image classification, building a convolutional neural network to classify images, and finally, learning how to improve model performance using transfer learning. When you're finished with this course, you'll have the skills and knowledge necessary to build your very own CNN using Caffe that'll help solve custom image classification problems. There are two prerequisites for the course. First would be an intermediate level knowledge of Python, and secondly, you'll also need a beginner to intermediate level understanding of machine learning. I hope you'll join me on this journey. To understand, create, and implement convolutional neural networks using Caffe, with the Deep Learning with Caffe course, at Pluralsight.